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researcher

Mário A. T. Figueiredo

4 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author4

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.LG4
same name
  • Mário A. T. Figueiredo — 23 papers, h 63
  • Mário A. T. Figueiredo — 12 papers
  • Mário A. T. Figueiredo — 2 papers
  • Mário A. T. Figueiredo — 1 paper, h 6
  • Mário A. T. Figueiredo — 1 paper, h 4
  • Mário A. T. Figueiredo — 1 paper, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20232026
most citedDiConStruct: Causal Concept-based Explanations through Black-Box Distillation

1 citations · 1 across the 2 of their papers we have counts for

collaborators

4 papers

cs.LG2026

Causal Discovery on Irregular Time Series

Martim Penim, Ricardo Ribeiro Pereira, Jacopo Bono +3

Causal discovery methods have shown strong performance in temporal systems, but they typically rely on regular and discrete lag structures, limiting their applicability to regularl…

cs.LG2024

Cost-Sensitive Learning to Defer to Multiple Experts with Workload Constraints

Jean V. Alves, Diogo Leitão, Sérgio Jesus +5

Learning to defer (L2D) aims to improve human-AI collaboration systems by learning how to defer decisions to humans when they are more likely to be correct than an ML classifier. E…

cs.LG2024★ 1 cited

DiConStruct: Causal Concept-based Explanations through Black-Box Distillation

Ricardo Moreira, Jacopo Bono, Mário Cardoso +3

Model interpretability plays a central role in human-AI decision-making systems. Ideally, explanations should be expressed using human-interpretable semantic concepts. Moreover, th…

cs.LG2023

FiFAR: A Fraud Detection Dataset for Learning to Defer

Jean V. Alves, Diogo Leitão, Sérgio Jesus +4

Public dataset limitations have significantly hindered the development and benchmarking of learning to defer (L2D) algorithms, which aim to optimally combine human and AI capabilit…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.